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- Michael Andrews
- COMPTNG 16A
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Based on 6 Users
TOP TAGS
- Engaging Lectures
- Appropriately Priced Materials
- Often Funny
- Would Take Again
- Is Podcasted
- Uses Slides
- Tolerates Tardiness
- Useful Textbooks
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
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Professor Andrews is the best programming professor I have had at UCLA as part of the PIC program getting a specialization in computing. His mathematical background makes him spend a great deal of time in class with understanding the semantics of Python (not obvious, especially when it comes to say NumPy broadcasting) and his midterm focused on that. However, his HWs are a joy, Once they are done, you see the power of Python from databases (Pandas), to image processing (numpy), to user interfaces (pyQt) to more basic stuff like string processing.
What is really remarkable about his class is that he covers a lot of ground, and so cannot teach any one topic (say numPy) in depth. But he taught us to search for documentation and many of his HWs use features he made us search for in. This is a great preparation, so it seems to me, for real life programming where you just cannot start programming till you "know it all" because there's just too much out there.
He's clearly a fun guy; he has a PhD from MIT in some abstract topology topics. he seems to love music, and through the class you get a sense of his likes in movies, music etc. I almost skipped this class to take a Matlab class but if I had I would have missed out on a great UCLA class. Take him, not just to get a grade but to learn a lot that is useful for life.
The TA Ben was very good as well.
Professor Andrews is probably the single best Professor I had at UCLA. His grading scheme is 70% HW, 10% Midterm and 15% Final with no homework drops. The A cutoff is a 95% raw score, but this should NOT deter you from taking his course. I didn't get a 100% on every homework and still ended with a 97% raw score. The homeworks are direct applications of what you learn in class. However, be aware that this mans is an absolute troll and makes you think of some edge cases. But with that said, once you get the desired output, it is extremely rewarding. The Final is very similar to the homeworks (I would strongly argue it was even easier than any of the homeworks maybe aside from homework 1). The midterm was something else. It was an assessment of do you actually know what is happening with your code and why your output is the way it is. This isn't some midterm that you can just take without watching the lectures. Luckily, he has the single most clear and engaging lecture of anyone I have every had at UCLA (next to great profs I've had such as Rubin). We went through basic Python, NumPy, PyQt, Pandas, and basic ML so there are plenty of applications that you are working with. Our TA, Ben, was really helpful with the homeworks. He moved at a relatively slow pace which I personally thought was too slow but better too slow than too fast. I'm extremely bummed this class is over and would love to take either a math or another PIC class with Professor Andrews in the near future.
Professor Andrews is engaging, knowledgeable, and British. He supplemented his lectures with a screen of various compilers with which he executed his programs, providing a very effective visual aid. He is also quite funny, often utilizing humor to hook his students into his examples to teach his concepts. Professor Andrews also made his students think about how programs execute, which is evidenced by his midterm primarily testing understanding of tracing. I would recommend him for this class! He will make sure you remember what he teaches.
To be honest I did not study enough for this class due to having many classes, which I quite regret since Dr. Andrews taught us very well. I found his lecture very useful whether you watch the recordings or attend Zoom classes. The homework and tests are fair, and so long as you proved you put some effort to solve the questions he is willing to give out many hints on how to solve/ fix bugs. Like others stated he covered many areas of Python, and the assignments made these applications looked very useful to real life! He is definitely a great professor if you want to enjoy programming even with little experience (It has been a year since I took C++ and yet he made everything very clear)
Professor Andrews is the best programming professor I have had at UCLA as part of the PIC program getting a specialization in computing. His mathematical background makes him spend a great deal of time in class with understanding the semantics of Python (not obvious, especially when it comes to say NumPy broadcasting) and his midterm focused on that. However, his HWs are a joy, Once they are done, you see the power of Python from databases (Pandas), to image processing (numpy), to user interfaces (pyQt) to more basic stuff like string processing.
What is really remarkable about his class is that he covers a lot of ground, and so cannot teach any one topic (say numPy) in depth. But he taught us to search for documentation and many of his HWs use features he made us search for in. This is a great preparation, so it seems to me, for real life programming where you just cannot start programming till you "know it all" because there's just too much out there.
He's clearly a fun guy; he has a PhD from MIT in some abstract topology topics. he seems to love music, and through the class you get a sense of his likes in movies, music etc. I almost skipped this class to take a Matlab class but if I had I would have missed out on a great UCLA class. Take him, not just to get a grade but to learn a lot that is useful for life.
The TA Ben was very good as well.
Professor Andrews is probably the single best Professor I had at UCLA. His grading scheme is 70% HW, 10% Midterm and 15% Final with no homework drops. The A cutoff is a 95% raw score, but this should NOT deter you from taking his course. I didn't get a 100% on every homework and still ended with a 97% raw score. The homeworks are direct applications of what you learn in class. However, be aware that this mans is an absolute troll and makes you think of some edge cases. But with that said, once you get the desired output, it is extremely rewarding. The Final is very similar to the homeworks (I would strongly argue it was even easier than any of the homeworks maybe aside from homework 1). The midterm was something else. It was an assessment of do you actually know what is happening with your code and why your output is the way it is. This isn't some midterm that you can just take without watching the lectures. Luckily, he has the single most clear and engaging lecture of anyone I have every had at UCLA (next to great profs I've had such as Rubin). We went through basic Python, NumPy, PyQt, Pandas, and basic ML so there are plenty of applications that you are working with. Our TA, Ben, was really helpful with the homeworks. He moved at a relatively slow pace which I personally thought was too slow but better too slow than too fast. I'm extremely bummed this class is over and would love to take either a math or another PIC class with Professor Andrews in the near future.
Professor Andrews is engaging, knowledgeable, and British. He supplemented his lectures with a screen of various compilers with which he executed his programs, providing a very effective visual aid. He is also quite funny, often utilizing humor to hook his students into his examples to teach his concepts. Professor Andrews also made his students think about how programs execute, which is evidenced by his midterm primarily testing understanding of tracing. I would recommend him for this class! He will make sure you remember what he teaches.
To be honest I did not study enough for this class due to having many classes, which I quite regret since Dr. Andrews taught us very well. I found his lecture very useful whether you watch the recordings or attend Zoom classes. The homework and tests are fair, and so long as you proved you put some effort to solve the questions he is willing to give out many hints on how to solve/ fix bugs. Like others stated he covered many areas of Python, and the assignments made these applications looked very useful to real life! He is definitely a great professor if you want to enjoy programming even with little experience (It has been a year since I took C++ and yet he made everything very clear)
Based on 6 Users
TOP TAGS
- Engaging Lectures (4)
- Appropriately Priced Materials (2)
- Often Funny (4)
- Would Take Again (3)
- Is Podcasted (3)
- Uses Slides (2)
- Tolerates Tardiness (2)
- Useful Textbooks (2)